The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized (or be conventional or well-known) in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also be inventions.
When a heavy processing job needs to be performed, service providers commonly provide processing through a server computing machine specified for performance of the job. For example, data processing jobs by workforce management services and providers may request audio data transcoding, big data analytics, screen recordings of workforce agent's operations and input during work (or other types of video compression, rendering, and/or processing), and the like to be performed by a server computing architecture. Server computing machines can process tasks for an arbitrary amount of time, which provides offline data processing that does not require high scalability (e.g., many operations) or a fast response time. However, fast response times require highly specialized and specification machines, each data processing instance can only handle a small amount of data during to heavy process (i.e., the instance has low scalability and is difficult to scale out), and strong machines that are highly specialized result in very high cost and overhead.
In contract, serverless cloud computing allows a cloud provider to allocate resources dynamically for data processing jobs. These resources are specified by the customer and therefore the customer is charged only for allocated resources and the run time for the data processing. This allows for high scalability and a fast response time. Conversely though, serverless computing architectures and technology are designed to handle light processing jobs. Each serverless cloud platform provides a range of processing units and their pricing model depends on the required disk space, execution time, central processing unit (CPU), and/or memory requested or delegated to the processing job. Thus, with a cheap serverless processing unit, the processing job may encounter high processing time or time out before the end of processing (as serverless processing units are limited in execution time). With a stronger or strongest processing unit, the processing job will be provided in a good response time but the cost will be high as serverless processing units are far more expensive than their equivalent server computing machines.